Salary for Senior-level / Expert Analytics Engineer in United States during 2022

Salary details

The average senior-level / expert Analytics Engineer salary lies between USD 122,500 and USD 190,000 in the United States. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Nov. 24, 2024

Salary trend

Top 20 Job Tags for Senior-level / Expert Analytics Engineer roles

The three most common job tag items assiciated with senior-level / expert Analytics Engineer job listings are SQL, Engineering and Python. Below you find a list of the 20 most occuring job tags in 2022 and the number of open jobs that where associated with them during that period:

SQL | 222 jobs Engineering | 218 jobs Python | 187 jobs Pipelines | 135 jobs Looker | 124 jobs Tableau | 104 jobs ETL | 101 jobs Snowflake | 101 jobs Data Analytics | 92 jobs Data pipelines | 87 jobs Airflow | 83 jobs Testing | 81 jobs AWS | 75 jobs BigQuery | 74 jobs Redshift | 70 jobs Git | 65 jobs Data warehouse | 65 jobs Business Intelligence | 63 jobs Computer Science | 63 jobs Data quality | 60 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert Analytics Engineer roles

The three most common job benefits and perks assiciated with senior-level / expert Analytics Engineer job listings are Career development, Startup environment and Health care. Below you find a list of the 20 most occuring job perks or benefits in 2022 and the number of open jobs that where offering them during that period:

Career development | 156 jobs Startup environment | 107 jobs Health care | 100 jobs Flex vacation | 87 jobs Flex hours | 85 jobs Team events | 79 jobs Equity / stock options | 66 jobs Parental leave | 62 jobs Competitive pay | 54 jobs Home office stipend | 44 jobs Salary bonus | 41 jobs Medical leave | 38 jobs 401(k) matching | 35 jobs Unlimited paid time off | 34 jobs Insurance | 33 jobs Wellness | 30 jobs Fitness / gym | 17 jobs Conferences | 11 jobs Gear | 10 jobs Transparency | 8 jobs

Salary Composition

In the United States, the salary composition for a Senior-level or Expert Analytics Engineer typically includes a combination of a fixed base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary often constitutes the majority of the total compensation package, ranging from 70% to 85%. Performance bonuses can vary significantly, often comprising 10% to 20% of the total compensation, depending on the company's performance and individual achievements. Additional remuneration, such as stock options, can be a significant part of the package in larger tech companies or startups, potentially making up 5% to 15% of the total compensation. The exact composition can vary based on the region, with tech hubs like Silicon Valley offering higher equity components, and the industry, with finance and healthcare often providing higher bonuses. Company size also plays a role, with larger companies typically offering more structured bonus and equity packages.

Increasing Salary

To increase your salary further from a Senior-level Analytics Engineer position, consider the following strategies:

• Specialization: Develop expertise in a niche area of AI/ML or data science that is in high demand, such as deep learning, natural language processing, or AI ethics.
• Leadership Roles: Transition into leadership or managerial roles, such as a Data Science Manager or Director of Analytics, which typically offer higher compensation.
• Continuous Learning: Stay updated with the latest technologies and methodologies in AI/ML, and consider pursuing advanced certifications or courses.
• Networking: Engage with professional networks and communities to learn about new opportunities and trends in the industry.
• Negotiation Skills: Improve your negotiation skills to better advocate for higher compensation during performance reviews or when switching jobs.

Educational Requirements

Most Senior-level Analytics Engineer positions require at least a bachelor's degree in a relevant field such as Computer Science, Data Science, Statistics, Mathematics, or Engineering. However, a master's degree or Ph.D. is often preferred, especially for roles that involve complex problem-solving and advanced analytical techniques. Advanced degrees can provide a deeper understanding of machine learning algorithms, statistical methods, and data management, which are crucial for this role.

Helpful Certifications

While not always mandatory, certain certifications can enhance your credentials and demonstrate your expertise to potential employers. Some valuable certifications include:

• Certified Analytics Professional (CAP): Validates your ability to transform data into valuable insights.
• Google Professional Machine Learning Engineer: Demonstrates proficiency in designing, building, and productionizing ML models.
• AWS Certified Machine Learning – Specialty: Shows expertise in using AWS services for machine learning.
• Microsoft Certified: Azure Data Scientist Associate: Validates skills in applying data science and machine learning techniques on Azure.

Required Experience

Typically, a Senior-level Analytics Engineer is expected to have at least 5 to 10 years of experience in data science, analytics, or a related field. This experience should include hands-on work with data analysis, machine learning model development, and data engineering. Experience in leading projects, mentoring junior team members, and collaborating with cross-functional teams is also highly valued.

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